Introduction of Majority Vote of Neighborhood Conditions for Sneak form Reinforcement Learning

AbstractChain Form Reinforcement Learning (CFRL) was proposed for a reinforcement learning agent using low memory. In this paper, we introduce Sneak Form Reinforcement Learning (SFRL). SFRL is the method where we improve CFRL in terms of Contextual Learning. If a sequence of state-action pairs has a shortest path, a SFRL agent cuts and saves the path. To improve the performance of SFRL, we introduce Majority Vote of Neighborhood Conditions for SFRL and call this method MVNC. Majority Vote of Neighborhood Conditions is the rule which agent in an unknown state selects an action not at random but with circumjacent information. Our methods were made a comparison to Q-Learning and CFRL in several easy simulations. We examined performance and discussed the best usage environment

A report on an Arts Administration internship with the New Orleans Film Festival, New Orleans, Louisiana, summer 2001

This paper comes from 180 hours of internship with the New Orleans Film Festival in Orleans Parish, New Orleans, Louisiana. During those hours of involvement with this organization, I focused on the competitive division of the festival that was then known as Cinema 16. In the course of events, questions arose concerning the issue of board involvement in the Cinema 16 jury process and the board\u27s administrative responsibilities. As it is with all human enterprise, there also is a continuously evolving attempt to improve methods. In the NOFF\u27s case there is an attempt to improve the judging of the entries. What should be the board\u27s role in that process? Cinema 16 should breathe life into the creative aspirations of fledgling filmmaker\u27s near and far. Does the New Orleans Fum Festival do all it can to make this a reality by vigorously marketing the selected films? Memberships became a focus when the disparity between the number of members in prior years and the number in 2001 appeared large. There were approximately 350 memberships in August of 2001, compared to 600 in 1999. There appeared to be a direct correlation between the number of memberships and mail-outs to the public. What other methods could be utilized to increase their numbers? Information is power. Answers to such questions would put the festival in the position of being proactive by giving them opportunity to further fulfill their mission as well as the capability to bring in more funds to continue their work. Time was given to exploring a university population as a viable market for new memberships. The staff shed light on the need for more services to offer prospective members. These major issues served to fulfill the purpose of the internship by opening up opportunities for experience in a nonprofit arts organization. The experience in its entirety brought to light the film festival\u27s impact on the concept that film is a credible art form celebrated by individuals everywhere. This paper should highlight the importance of the various processes, not only in giving that organization credibility but also in aiding it in making the impact it wishes to on its immediate and global community

Pension Fund Evictions: Lessons for Housing and Labor

In this dissertation I analyze an institutional investor portfolio of over-leveraged multifamily rental housing in East Palo Alto, California to demonstrate how changing forms of landlordism produce both new and familiar targets for tenants organizing against displacement and for housing security. Venture capital investors in the first decade of the 2000s exploited the Silicon Valley regional conditions of racial exclusion, uneven development, and municipal rent control. I introduce the legacy of Black political organization in East Palo Alto as a way of contextualizing the tenants’ and the city leaders’ response to the monopoly investment purchase. The structure of this rental portfolio demonstrates the multiple actors involved in such large-scale residential investments, including institutional state pension funds, high-net worth individuals, local and international lenders, money managers, and the Security and Exchange Commission. The case study analysis considers how tenants, advocates, and a local union representing shareholders in the country’s largest pension, the California Public Employees’ Retirement System (CalPERS), mobilized city and state officials to exert influence over these targets, focusing on the institutional investor in particular, albeit with limited success. This case finds that venture capital investors backed by public pension funds exacerbated the escalating renter crisis in East Palo Alto, and elsewhere. I suggest that the findings from this case study, particularly those detailing the points of leverage available to tenants to target public pension funds, as well as the power of cities, bear lessons for tenants organizing in other large-scale multifamily rental portfolios and bundled scattered site single-family real estate owned (REO) foreclosure-to-rental portfolios. The analysis concludes by drawing from principles of housing security and offering what a coalitional, labor/community, racial justice politics for “the right to the city” might entail when taking into account changing conditions of investor landlordism

TOWARDS A HOLISTIC EFFICIENT STACKING ENSEMBLE INTRUSION DETECTION SYSTEM USING NEWLY GENERATED HETEROGENEOUS DATASETS

With the exponential growth of network-based applications globally, there has been a transformation in organizations\u27 business models. Furthermore, cost reduction of both computational devices and the internet have led people to become more technology dependent. Consequently, due to inordinate use of computer networks, new risks have emerged. Therefore, the process of improving the speed and accuracy of security mechanisms has become crucial.Although abundant new security tools have been developed, the rapid-growth of malicious activities continues to be a pressing issue, as their ever-evolving attacks continue to create severe threats to network security. Classical security techniquesfor instance, firewallsare used as a first line of defense against security problems but remain unable to detect internal intrusions or adequately provide security countermeasures. Thus, network administrators tend to rely predominantly on Intrusion Detection Systems to detect such network intrusive activities. Machine Learning is one of the practical approaches to intrusion detection that learns from data to differentiate between normal and malicious traffic. Although Machine Learning approaches are used frequently, an in-depth analysis of Machine Learning algorithms in the context of intrusion detection has received less attention in the literature.Moreover, adequate datasets are necessary to train and evaluate anomaly-based network intrusion detection systems. There exist a number of such datasetsas DARPA, KDDCUP, and NSL-KDDthat have been widely adopted by researchers to train and evaluate the performance of their proposed intrusion detection approaches. Based on several studies, many such datasets are outworn and unreliable to use. Furthermore, some of these datasets suffer from a lack of traffic diversity and volumes, do not cover the variety of attacks, have anonymized packet information and payload that cannot reflect the current trends, or lack feature set and metadata.This thesis provides a comprehensive analysis of some of the existing Machine Learning approaches for identifying network intrusions. Specifically, it analyzes the algorithms along various dimensionsnamely, feature selection, sensitivity to the hyper-parameter selection, and class imbalance problemsthat are inherent to intrusion detection. It also produces a new reliable dataset labeled Game Theory and Cyber Security (GTCS) that matches real-world criteria, contains normal and different classes of attacks, and reflects the current network traffic trends. The GTCS dataset is used to evaluate the performance of the different approaches, and a detailed experimental evaluation to summarize the effectiveness of each approach is presented. Finally, the thesis proposes an ensemble classifier model composed of multiple classifiers with different learning paradigms to address the issue of detection accuracy and false alarm rate in intrusion detection systems

Fitting-in: How Formerly Incarcerated New York City Black Men Define Success Post-Prison

The problem of community reintegration emerged following the rise of the US prison population, which began in in the 1970s, disproportionately affecting US-born African American men. In this qualitative study, the researcher examined the perceptions of 17 formerly incarcerated New York City African American men to understand how they defined post-prison success after having been in the community at least three years in the wake of the era of mass (hyper) incarceration. During the study, the researcher employed a constructivist grounded theory (Charmaz, 2006) approach using data from semi-structured interviews to identify factors that enabled these African American men to make the social and psychological adjustments needed to get on with their lives post-release. Success, as defined by the men in the study, meant fitting-in to their home communities as if they had never been in prison. The findings of this study demonstrate that success is a construct inclusive of material, social, and psychological components. A number of themes emerged from the data that respondents attached importance to that the researcher linked to each component of success and subsequently related to the fitting-in process. The eligibility requirements for this study, which limited participation to men who had been out of prison at least three years, restricted generalizability of the results and suggest that length of time since release likely influenced definitions of success. This dissertation concludes proposing research to examine potentially influencing issues related to time upon definitions of success, post-prison achievements, and the psychological effects of the incarceration experience and its relationship to African American men’s post-prison experiences. These findings can enhance social work practice with justice-involved African American men, enable social workers to better understand this population, and encourage the development of additional methods to address the psychological challenges related to post-prison adjustment likely to contribute to their well-being

Property Tax and School Choice in Pennsylvania K-12 Education

For many years now, Pennsylvanian lawmakers have debated the merits of changing the funding method of public schools, with the elimination of property taxes drawing headlines in the media but never being realized through legislative amendments to the school funding formulas. Still today, legislation is being proposed to eliminate property tax as a funding source. The purpose of this study is to determine whether there is demographic or geographic support for these efforts among those who budget and utilize these funds: school board members. The theoretical framework employed will be that of social choice theory. A survey was conducted among school board members from the 501 individual districts in Pennsylvania to determine if there was support for a change to sales and income taxes in lieu of property taxes for school funding and subjected to analysis using SPSS via independent samples Kruskal-Wallis H and Mann Whitney-U testing, along with Crosstab analysis. Additional questions explore support for school choice and voucher systems with Pennsylvania K-12 education. The findings of this study showed that there exists support among certain geographic and demographic groups for these concepts

Columbia Chronicle (10/31/2011)

Student newspaper from October 31, 2011 entitled The Columbia Chronicle. This issue is 44 pages and is listed as Volume 47, Number 9. Cover story: Funds and sprits raised Editor-in-Chief: Brianna Wellenhttps://digitalcommons.colum.edu/cadc_chronicle/1831/thumbnail.jp